Valvular Heart Disease PatientsNCT07023510
The VALVE-AI Trial
A study testing AI-ECG driven echocardiography in people with Valvular Heart Disease Patients, run by National Defense Medical Center, Taiwan at 1 site in Taiwan.
Trial summary
The goal of this clinical trial is to learn if an artificial intelligence-powered electrocardiogram (AI-ECG) can help detect moderate or severe valvular heart diseases (VHD) in adults. Read more about this study
- Who is it for?
- Ages 60 to 85 years
- Conditions the study is for
- Valvular Heart Disease Patients
- What is being tested?
- AI-ECG driven echocardiography
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 8,648 participants
- Where
- 1 siteTaiwan
- Study dates
- 1 Jul 2025to 1 Jul 2026
- Phase
- Interventional
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 60 to 85 years
- All sexes
- No healthy volunteers
- Adult, Older adult
Who may be able to join
- At least one 12-lead ECG within 1 year
- Age 60-85 years of age
Who cannot join
- Documented echocardiography within 3 years before indexed ECG
- Any known valvular heart disease
- History of any valvular surgery
- Post-heart transplant
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
Taiwan1 site, 1 recruiting
- Recruiting
Tri-Service General Hospital
Taipei
Yuan-Hao Chen, +886-2-87923311, chenyh178@gmail.com
About this study
Official title: VALidation of Screening Valvular Heart Disease Using Electrocardiogram Powered by Artificial Intelligence: A Randomized Controlled Trial
The goal of this clinical trial is to learn if an artificial intelligence-powered electrocardiogram (AI-ECG) can help detect moderate or severe valvular heart diseases (VHD) in adults. The main question it aims to answer is:
．Can AI-ECG screening identify patients with significant heart valve diseases who may benefit from early echocardiography? Researchers will compare the rate of moderate or severe VHD detection between the experimental group and the control group to see if AI-ECG improve the detection rate of significant VHD.
Read more
Participants will:
- Be classified as high- or low-risk for VHD using an AI-ECG system
- In the experimental group, high-risk participants will receive echocardiography based on AI-ECG results
- In the control group, usual clinical care will be provided without routine echocardiography for AI-ECG high-risk results.
Read the detailed description
This randomized controlled trial investigates the effectiveness of an artificial intelligence-powered electrocardiogram (AI-ECG) system for early screening of moderate or severe valvular heart disease (VHD) in adults receiving routine ECG examinations. The study population consists of adult outpatients undergoing a standard 12-lead ECG for any clinical indication. Each ECG is analyzed by a validated deep learning algorithm that automatically classifies the patient's risk for significant VHD.
Participants identified as high-risk by the AI-ECG system are randomized into either an experimental group or a control group. In the experimental group, high-risk participants undergo transthoracic echocardiography to confirm or exclude moderate or severe VHD. In the control group, high-risk participants continue with usual clinical care without additional echocardiographic screening based solely on the AI-ECG result. Low-risk participants in both groups receive routine care without additional intervention.
The primary aim is to determine whether AI-guided ECG screening, coupled with targeted echocardiography in the experimental group, increases the detection rate of clinically significant VHD compared to usual care. Secondary objectives include evaluating the impact on timely diagnosis, downstream clinical management, and the feasibility of integrating AI-ECG screening into routine outpatient workflows.
The study will follow participants for up to 90 days post-randomization to assess the detection rate and related outcomes.
- Conditions
- Valvular Heart Disease Patients
- Being tested
- AI-ECG driven echocardiography
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
AI-ECG driven echocardiographyDiagnostic test
The intervention utilizes a previously validated deep learning model based on 12-lead electrocardiogram (ECG) data to screen for moderate-to-severe valvular heart diseases (VHD). The model processes raw ECG signals and integrates age and sex to enhance prediction. (doi: 10.18632/aging.205835.) Participants identified as high-risk for any moderate-to-severe VHD by the algorithm of artificial intelligence-powered electrocardiogram (AI-ECG) in this intervention arm will receive transthoracic echocardiography to confirm diagnosis and guide further management.
| Study group | Role | What they receive |
|---|---|---|
| AI-ECG | Experimental | Participants whose electrocardiogram is classified as high-risk for moderate or severe valvular heart disease (VHD) by the artificial intelligence-powered electrocardiogram (AI-ECG) system will receive additional transthoracic echocardiography, regardless of whether the treating physician suspects VHD based on symptoms or physical examination.
Low-risk participants continue with routine care without additional intervention. Receives: Diagnostic Test: AI-ECG driven echocardiography |
| Usual care | No intervention | Participants whose electrocardiogram is classified as high-risk for moderate or severe valvular heart diseases (VHD) by the artificial intelligence-powered electrocardiogram (AI-ECG) system receive standard care according to routine clinical practice. Transthoracic echocardiography is arranged only if the treating physician deems it clinically necessary based on the symptoms, physical examination, , or other non-AI findings. Low-risk participants continue with routine care without additional intervention. |
What is being measured
The primary outcome is the main question the study is designed to answer.
Composite of Any Moderate or Severe VHD by Echocardiography
The composite endpoint is defined as detecting any moderate or severe VHD by echocardiography, including mitral regurgitation (MR), aortic regurgitation (AR), aortic stenosis (AS), and tricuspid regurgitation (TR).
Measured: Within 90 days after randomization.
Secondary outcomes (5)
Number of Participants with Moderate or Severe MR by Echocardiography
Measured: Within 90 days after randomization.
Number of Participants with Moderate or Severe AR by Echocardiography
Measured: Within 90 days after randomization.
Number of Participants with Moderate or Severe AS by Echocardiography
Measured: Within 90 days after randomization.
Number of Participants with Moderate or Severe TR by Echocardiography
Measured: Within 90 days after randomization.
Number of Participants with Other Cardiac Diseases by Echocardiography
The endpoint measures the number and proportion of atrial septal defect, ventricular septal defect, cardiac tamponade, and large pericardial effusion.
Measured: Within 90 days after randomization.
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted17 Jun 2025
- Study start1 Jul 2025 (estimated)
- Primary completion1 Jul 2026 (estimated)
- Study completion1 Jul 2026 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (1)Papers the sponsor has linked to this study.
- Other trials for Valvular Heart Disease PatientsStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Screening
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- None (open label)
- Enrolment
- 8,648 participants (estimated)
Sponsor and investigators
- Lead sponsor
- National Defense Medical Center, Taiwan
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Yu-Lan Liu, National Defense Medical Center, Taiwan
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07023510
- Sponsor's protocol ID
- VALVE-AI RCT
- Status last verified
- Jun 2025
- First submitted
- 8 Jun 2025
- Last updated
- 26 Jun 2025
- Results posted
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Publications
Lin YT, Lin CS, Tsai CS, Tsai DJ, Lou YS, Fang WH, Lee YT, Lin C. Comprehensive clinical application analysis of artificial intelligence-enabled electrocardiograms for screening multiple valvular heart diseases. Aging (Albany NY). 2024 May 16;16(10):8717-8731. doi: 10.18632/aging.205835. Epub 2024 May 16.
PubMed 38761181
Study at a glance
From the registry record, last updated by the sponsor on 26 Jun 2025. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- VALidation of Screening Valvular Heart Disease Using Electrocardiogram Powered by Artificial Intelligence: A Randomized Controlled Trial
- ClinicalTrials.gov ID
- NCT07023510
- Acronym / sponsor ID
- VALVE-AI RCT
- Conditions
- Valvular Heart Disease Patients
- Study type
- Interventional
- Recruitment status
- Recruiting
- Enrolment
- 8,648 participants (estimated)
- Lead sponsor
- National Defense Medical Center, TaiwanUniversity, hospital or other
- Study start
- 1 Jul 2025 (estimated)
- Primary completion
- 1 Jul 2026 (estimated)
- Study completion
- 1 Jul 2026 (estimated)
- First posted
- 17 Jun 2025 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
The goal of this clinical trial is to learn if an artificial intelligence-powered electrocardiogram (AI-ECG) can help detect moderate or severe valvular heart diseases (VHD) in adults. The main question it aims to answer is:
．Can AI-ECG screening identify patients with significant heart valve diseases who may benefit from early echocardiography? Researchers will compare the rate of moderate or severe VHD detection between the experimental group and the control group to see if AI-ECG improve the detection rate of significant VHD.
Participants will:
- Be classified as high- or low-risk for VHD using an AI-ECG system
- In the experimental group, high-risk participants will receive echocardiography based on AI-ECG results
- In the control group, usual clinical care will be provided without routine echocardiography for AI-ECG high-risk results.
Detailed description
This randomized controlled trial investigates the effectiveness of an artificial intelligence-powered electrocardiogram (AI-ECG) system for early screening of moderate or severe valvular heart disease (VHD) in adults receiving routine ECG examinations. The study population consists of adult outpatients undergoing a standard 12-lead ECG for any clinical indication. Each ECG is analyzed by a validated deep learning algorithm that automatically classifies the patient's risk for significant VHD.
Participants identified as high-risk by the AI-ECG system are randomized into either an experimental group or a control group. In the experimental group, high-risk participants undergo transthoracic echocardiography to confirm or exclude moderate or severe VHD. In the control group, high-risk participants continue with usual clinical care without additional echocardiographic screening based solely on the AI-ECG result. Low-risk participants in both groups receive routine care without additional intervention.
The primary aim is to determine whether AI-guided ECG screening, coupled with targeted echocardiography in the experimental group, increases the detection rate of clinically significant VHD compared to usual care. Secondary objectives include evaluating the impact on timely diagnosis, downstream clinical management, and the feasibility of integrating AI-ECG screening into routine outpatient workflows.
The study will follow participants for up to 90 days post-randomization to assess the detection rate and related outcomes.
Study design
- Primary purpose
- Screening
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- None (open label)
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| AI-ECG | Experimental | Diagnostic Test: AI-ECG driven echocardiographyParticipants whose electrocardiogram is classified as high-risk for moderate or severe valvular heart disease (VHD) by the artificial intelligence-powered electrocardiogram (AI-ECG) system will receive additional transthoracic echocardiography, regardless of whether the treating physician suspects VHD based on symptoms or physical examination. Low-risk participants continue with routine care without additional intervention. |
| Usual care | No intervention | –Participants whose electrocardiogram is classified as high-risk for moderate or severe valvular heart diseases (VHD) by the artificial intelligence-powered electrocardiogram (AI-ECG) system receive standard care according to routine clinical practice. Transthoracic echocardiography is arranged only if the treating physician deems it clinically necessary based on the symptoms, physical examination, , or other non-AI findings. Low-risk participants continue with routine care without additional intervention. |
Who may qualify
- Ages
- 60 to 85 years
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (2 listed)
- At least one 12-lead ECG within 1 year
- Age 60-85 years of age
Key exclusion criteria (4 listed)
- Documented echocardiography within 3 years before indexed ECG
- Any known valvular heart disease
- History of any valvular surgery
- Post-heart transplant
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| AI-ECG driven echocardiographyThe intervention utilizes a previously validated deep learning model based on 12-lead electrocardiogram (ECG) data to screen for moderate-to-severe valvular heart diseases (VHD). The model processes raw ECG signals and integrates age and sex to enhance prediction. (doi: 10.18632/aging.205835.) Participants identified as high-risk for any moderate-to-severe VHD by the algorithm of artificial intelligence-powered electrocardiogram (AI-ECG) in this intervention arm will receive transthoracic echocardiography to confirm diagnosis and guide further management. | Diagnostic test | AI-ECG |
Primary outcome
Composite of Any Moderate or Severe VHD by Echocardiography
Time frame: Within 90 days after randomization.
The composite endpoint is defined as detecting any moderate or severe VHD by echocardiography, including mitral regurgitation (MR), aortic regurgitation (AR), aortic stenosis (AS), and tricuspid regurgitation (TR).
5 secondary outcomes
Number of Participants with Moderate or Severe MR by Echocardiography
Time frame: Within 90 days after randomization.
Number of Participants with Moderate or Severe AR by Echocardiography
Time frame: Within 90 days after randomization.
Number of Participants with Moderate or Severe AS by Echocardiography
Time frame: Within 90 days after randomization.
Number of Participants with Moderate or Severe TR by Echocardiography
Time frame: Within 90 days after randomization.
Number of Participants with Other Cardiac Diseases by Echocardiography
Time frame: Within 90 days after randomization.
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 26 Jun 2025.
- Results publication: PubMed 38761181Lin YT, Lin CS, Tsai CS, Tsai DJ, Lou YS, Fang WH, Lee YT, Lin C. Comprehensive clinical application analysis of artificial intelligence-enabled electrocardiograms for screening multiple valvular heart diseases. Aging (Albany NY). 2024 May 16;16(10):8717-8731. doi: 10.18632/aging.205835. Epub 2024 May 16.
- Individual participant dataSharing planned: No
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part.
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing AI-ECG driven echocardiography in people with Valvular Heart Disease Patients, run by National Defense Medical Center, Taiwan at 1 site in Taiwan.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 2 inclusion and 4 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: looking for participants now, as of the sponsor's last update on 26 Jun 2025. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in Taiwan. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact Chin Lin (+886-2-8792-3100 ext. 18574, xup6fup0629@gmail.com), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Composite of Any Moderate or Severe VHD by Echocardiography (time frame: Within 90 days after randomization.). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT07023510, which also lists 1 linked publication.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 26 Jun 2025.